Expectancy-related changes in firing of dopamine neurons depend on hippocampus.

The orbitofrontal cortex (OFC) and hippocampus (HC) both contribute to the cognitive maps that support flexible behavior. Previously, we used the dopamine neurons to measure the functional role of OFC. We recorded midbrain dopamine neurons as rats performed an odor-based choice task, in which expected rewards were manipulated across blocks. We found that ipsilateral OFC lesions degraded dopaminergic prediction errors, consistent with reduced resolution of the task states. Here we have repeated this experiment in male rats with ipsilateral HC lesions. The results show HC also shapes the task states, however unlike OFC, which provides information local to the trial, the HC is necessary for estimating upper-level hidden states that distinguish blocks. The results contrast the roles of the OFC and HC in cognitive mapping and suggest that the dopamine neurons access rich information from distributed regions regarding the environment's structure, potentially enabling this teaching signal to support complex behaviors.

The aging heart in focus: The advanced understanding of heart failure with preserved ejection fraction.

Heart failure with preserved ejection fraction (HFpEF) accounts for 50 % of heart failure (HF) cases, making it the most common type of HF, and its prevalence continues to increase in the aging society. HFpEF is a systemic syndrome resulting from many risk factors, such as aging, metabolic syndrome, and hypertension, and its clinical features are highly heterogeneous in different populations. HFpEF syndrome involves the dysfunction of multiple organs, including the heart, lung, muscle, and vascular system. The heart shows dysfunction of various cells, including cardiomyocytes, endothelial cells, fibroblasts, adipocytes, and immune cells. The complex etiology and pathobiology limit experimental research on HFpEF in animal models, delaying a comprehensive understanding of the mechanisms and making treatment difficult. Recently, many scientists and cardiologists have attempted to improve the clinical outcomes of HFpEF. Recent advances in clinically related animal models and systemic pathology studies have improved our understanding of HFpEF, and clinical trials involving sodium-glucose cotransporter 2 inhibitors have significantly enhanced our confidence in treating HFpEF. This review provides an updated comprehensive discussion of the etiology and pathobiology, molecular and cellular mechanisms, preclinical animal models, and therapeutic trials in animals and patients to enhance our understanding of HFpEF and improve clinical outcomes.

Efficacy and safety of transarterial chemoembolization alone compared to its combination with anlotinib among patients with intermediate or advanced stage hepatocellular carcinoma: a phase II randomized controlled trial.

Background: Anlotinib hydrochloride is a potent oral multitargeted tyrosine kinase inhibitor that targets VEGFR1-3, FGFR1-4, and PDGFR α/ß, demonstrating significant antiangiogenic activity. Transcatheter arterial chemoembolization (TACE) is considered the effective treatment for intermediate/advanced hepatocellular carcinoma (HCC), which remains a major global health challenge. This study evaluated the relative efficacy and safety of combining anlotinib with TACE against the standard TACE monotherapy among patients with intermediate or advanced HCC. Methods: This phase II randomized controlled trial included 38 patients diagnosed with intermediate or advanced HCC. Patients were randomly assigned to receive either TACE in combination with anlotinib or TACE alone. The primary endpoint of the study was progression-free survival (PFS), while secondary endpoints included overall survival (OS), objective response rate (ORR), disease control rate (DCR), and safety. This trial aimed to determine whether the addition of anlotinib could extend PFS and improve other clinical outcomes compared to TACE alone. Results: The median PFS for patients treated with TACE and anlotinib was significantly longer at 11.04 months compared to 6.87 months in the TACE-alone group [hazard ratio (HR) 0.46; P=0.02], indicating a robust enhancement in disease management. Although the median OS was not reached at the time of analysis, early trends suggest potential improvement. Both treatment groups had comparable ORR and DCR, demonstrating effective disease control. The safety profile of the combined treatment was manageable, with side effects similar in nature to those observed with TACE alone but not significantly more severe, thus maintaining patient quality of life. Conclusions: The addition of anlotinib to TACE appears to provide a safe and effective therapeutic benefit for patients with intermediate or advanced-stage HCC. However, longer follow-up is needed for a more comprehensive efficacy assessment. Trial Registration: ClinicalTrials.gov NCT04066543.

Regulation of transcription factor function by purinergic signalling in cardiovascular diseases.

Cardiovascular diseases (CVDs), including hypertension, atherosclerosis, myocardial ischemia, and myocardial infarction, constitute the primary cause of mortality worldwide. Transcription factors play critical roles in the development of CVDs and contribute to the pathophysiology of these diseases by coordinating the transcription of many genes involved in inflammation, oxidative stress, angiogenesis, and glycolytic metabolism. One important regulator of hemostasis in both healthy and pathological settings has been identified as a purinergic signalling pathway. Research has demonstrated that several signalling networks implicated in the pathophysiology of CVDs are formed by transcription factors that are regulated by purinergic substances. Here, we briefly summarize the roles and mechanisms of the transcription factors regulated by purinergic pathways in various types of CVD. This information will be essential for discovering novel approaches for CVD treatment and prevention.

Efficacy and safety of ramucirumab for gastric or gastro-esophageal junction adenocarcinoma: a systematic review and meta-analysis.

PURPOSE: Based on the comparison of ramucirumab monoclonal antibody with control treatments in randomized controlled trials, this study aims to elucidate the role of ramucirumab monoclonal antibody in cancer therapy and its potential side effects, providing scientific evidence for clinical treatment. METHODS: PubMed, Embase, Cochrane, and Web of Science were searched systematically to obtain the trials on ramucirumab in the treatment of gastric or gastroesophageal junction (GEJ) adenocarcinoma up to April 13, 2023. We included randomized controlled trials (RCTs) evaluating the efficacy and safety of ramucirumab as monotherapy and in combination with other chemotherapy agents as interventions for treating gastric or gastroesophageal junction (GEJ) adenocarcinoma. RESULTS: After screening 2200 studies, we finally included 8 eligible studies (involving a total of 3,283 participants). Meta-analysis results showed that compared to the control group, ramucirumab monotherapy significantly improved overall survival (OS) (hazard ratio [HR] = 0.77, 95% confidence interval [CI] [0.67, 0.89]) and progression-free survival (PFS) (HR = 0.48, 95% CI [0.40, 0.58]). Similar results were obtained for ramucirumab combined with paclitaxel. In the treatment combining ramucirumab with paclitaxel, compared to monotherapy, three severe adverse reactions (grade ≥ 3) were observed with significantly increased risks (OR > 2). These include proteinuria (OR = 5.37, 95% CI [1.22, 23.54]), hypertension (OR = 4.02, 95% CI [2.63, 6.14]), and gastrointestinal perforation (OR = 4.64, 95% CI [1.00, 21.60]). Subgroup analysis further indicated that ramucirumab is effective in both non-East Asian and East Asian populations, with East Asian patients more prone to developing proteinuria, while having a lower incidence of hypertension. Additionally, ramucirumab demonstrated comparable efficacy between first-line and second-line treatments, with a higher incidence of proteinuria observed in second-line therapy. CONCLUSION: Ramucirumab significantly improves the prognosis of patients with gastric or gastroesophageal junction adenocarcinoma. When used in combination with paclitaxel, close monitoring of adverse reactions such as proteinuria (especially in East Asian populations), hypertension (especially in non-East Asian populations), and gastrointestinal perforation is essential.

Contrastive Unsupervised Representation Learning With Optimize-Selected Training Samples.

Contrastive unsupervised representation learning (CURL) is a technique that seeks to learn feature sets from unlabeled data. It has found widespread and successful application in unsupervised feature learning, with the design of positive and negative pairs serving as the type of data samples. While CURL has seen empirical successes in recent years, there is still room for improvement in terms of the pair data generation process. This includes tasks such as combining and re-filtering samples, or implementing transformations among positive/negative pairs. We refer to this as the sample selection process. In this article, we introduce an optimized pair-data sample selection method for CURL. This method efficiently ensures that the two types of sampled data (similar pair and dissimilar pair) do not belong to the same class. We provide a theoretical analysis to demonstrate why our proposed method enhances learning performance by analyzing its error probability. Furthermore, we extend our proof into PAC-Bayes generalization to illustrate how our method tightens the bounds provided in previous literature. Our numerical experiments on text/image datasets show that our method achieves competitive accuracy with good generalization bounds.

Dopamine and acetylcholine correlations in the nucleus accumbens depend on behavioral task states.

Dopamine in the nucleus accumbens ramps up as animals approach desired goals. These ramps have received intense scrutiny because they seem to violate long-held hypotheses on dopamine function. Furthermore, it has been proposed that they are driven by local acetylcholine release, i.e., that they are mechanistically separate from dopamine signals related to reward prediction errors. Here, we tested this hypothesis by simultaneously recording accumbal dopamine and acetylcholine signals in rats executing a task involving motivated approach. Contrary to recent reports, we found that dopamine ramps were not coincidental with changes in acetylcholine. Instead, we found that acetylcholine could be positively, negatively, or uncorrelated with dopamine depending on whether the task phase was determined by a salient cue, reward prediction error, or active approach, respectively. Our results suggest that accumbal dopamine and acetylcholine are largely independent but may combine to engage different postsynaptic mechanisms depending on the behavioral task states.

Re-tear after arthroscopic rotator cuff repair can be predicted using deep learning algorithm.

The application of artificial intelligence technology in the medical field has become increasingly prevalent, yet there remains significant room for exploration in its deep implementation. Within the field of orthopedics, which integrates closely with AI due to its extensive data requirements, rotator cuff injuries are a commonly encountered condition in joint motion. One of the most severe complications following rotator cuff repair surgery is the recurrence of tears, which has a significant impact on both patients and healthcare professionals. To address this issue, we utilized the innovative EV-GCN algorithm to train a predictive model. We collected medical records of 1,631 patients who underwent rotator cuff repair surgery at a single center over a span of 5 years. In the end, our model successfully predicted postoperative re-tear before the surgery using 62 preoperative variables with an accuracy of 96.93%, and achieved an accuracy of 79.55% on an independent external dataset of 518 cases from other centers. This model outperforms human doctors in predicting outcomes with high accuracy. Through this methodology and research, our aim is to utilize preoperative prediction models to assist in making informed medical decisions during and after surgery, leading to improved treatment effectiveness. This research method and strategy can be applied to other medical fields, and the research findings can assist in making healthcare decisions.

Phthalate exposure aggravates periodontitis by activating NFκB pathway.

BACKGROUND: Phthalates are widely used plasticizers, which were identified as risk factors in the development of many human diseases. However, the effects of phthalates in the periodontitis are unknown. We aimed to investigated the relationship of periodontitis and phthalate exposure as well as the underlying mechanisms. MATERIALS AND METHODS: Univariate and multivariate logistic regressions were employed to evaluate the association between phthalate metabolites and periodontitis. The generalized additive model and piecewise logistic regression were conducted to investigate the dose-response relationship. Cell and animal models were used to explore the role and mechanism of DEHP in the development of periodontitis. Transcriptome sequencing, bioinformatics analysis, western blot, immunofluorescence and mice model of periodontitis were also employed. RESULTS: MEHP (OR 1.14, 95% CI 1.05-1.24), MCPP (OR 1.08, 95% CI 1.00-1.17), MEHHP (OR 1.18, 95% CI 1.08-1.29), MEOHP (OR 1.18, 95% CI 1.07-1.29), MiBP (OR 1.15, 95% CI 1.04-1.28), and MECPP (OR 1.20, 95% CI 1.09-1.32) were independent risk factors. And MEHHP, the metabolite of DEHP, showed the relative most important effects on periodontitis with the highest weight (0.34) among all risk factors assessed. And the increase of inflammation and the activation of NFκB pathway in the periodontitis model mice and cells were observed. CONCLUSION: Exposure to multiple phthalates was positively associated with periodontitis in US adults between 30 and 80 years old. And DEHP aggravated inflammation in periodontitis by activating NFκB pathway.

Regulating Cholesterol in Tumorigenesis: A Novel Paradigm for Tumor Nanotherapeutics.

During the past decade, "membrane lipid therapy", which involves the regulation of the structure and function of tumor cell plasma membranes, has emerged as a new strategy for cancer treatment. Cholesterol is an important component of the tumor plasma membrane and serves an essential role in tumor initiation and progression. This review elucidates the role of cholesterol in tumorigenesis (including tumor cell proliferation, invasion/metastasis, drug resistance, and immunosuppressive microenvironment) and elaborates on the potential therapeutic targets for tumor treatment by regulating cholesterol. More meaningfully, this review provides an overview of cholesterol-integrated membrane lipid nanotherapeutics for cancer therapy through cholesterol regulation. These strategies include cholesterol biosynthesis interference, cholesterol uptake disruption, cholesterol metabolism regulation, cholesterol depletion, and cholesterol-based combination treatments. In summary, this review demonstrates the tumor nanotherapeutics based on cholesterol regulation, which will provide a reference for the further development of "membrane lipid therapy" for tumors.

Untargeted Metabolomics Analysis of Gingival Tissue in Patients with Severe Periodontitis.

The purpose of this study was to determine potential metabolic biomarkers and therapeutic drugs in the gingival tissue of individuals with periodontitis. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) were used to analyze the gingival tissue samples from 20 patients with severe periodontitis and 20 healthy controls. Differential metabolites were identified using variable important in projection (VIP) values from the orthogonal partial least squares discrimination analysis (OPLS-DA) model and then verified for significance between groups using a two-tailed Student's t test. In total, 65 metabolites were enriched in 33 metabolic pathways, with 40 showing a significant increase and 25 expressing a significant decrease. In addition, it was found that patients with severe periodontitis have abnormalities in metabolic pathways, such as glucose metabolism, purine metabolism, amino acid metabolism, and so on. Furthermore, based on a multidimensional analysis, 12 different metabolites may be the potential biomarkers of severe periodontitis. The experiment's raw data have been uploaded to the MetaboLights database, and the project number is MTBLS8357. Moreover, osteogenesis differentiation characteristics were detected in the selected metabolites. The findings may provide a basis for the study of diagnostic biomarkers and therapeutic metabolites in severe periodontitis.

Bomidin attenuates inflammation of periodontal ligament stem cells and periodontitis in mice via inhibiting ferroptosis.

AIM: Periodontitis is a prevalent oral immunoinflammatory condition that is distinguished by the compromised functionality of periodontal ligament stem cells (PDLSCs). Bomidin, a new recombinant antimicrobial peptide (AMP), exhibits antibacterial properties and modulates immune responses. Nevertheless, the precise anti-inflammatory impact of bomidin in periodontitis has yet to be fully elucidated. Thus, the study aimed to clarified the role of bomidin in modulating inflammation and its underlying mechanisms. METHODS: TNF-α was applied to treating PDLSCs for establishing a cell model of periodontitis. Bomidin, RSL3, ML385 and cycloheximide were also used to treat PDLSCs. Transcriptome sequencing, RT-qPCR, western blot, immunofluorescence, immunohistochemistry, Fe2+ detection probe, molecular docking, Co-IP assay, ubiquitination assay and murine models of periodontitis were used. RESULTS: Our study demonstrated that bomidin effectively suppressed inflammation in PDLSCs stimulated by TNF-α, through down-regulating the MAPK and NF-κB signaling pathways. Furthermore, bomidin exerted inhibitory effects on ferroptosis and activated the Keap1/Nrf2 pathway in the TNF-α group. There is a strong likelihood of bonding bomidin with Keap1 protein, which facilitated the degradation of Keap1 protein via the ubiquitin-proteasome pathway, leading to an enhanced translocation of Nrf2 protein to the nucleus. CONCLUSIONS: Bomidin can directly bond to Keap1 protein, resulting in the degradation of Keap1 through the ubiquitin-proteasome pathway, thereby further activating the Keap1/Nrf2 pathway. The upregulation of the Keap1/Nrf2 signaling pathway was found to contribute to the suppression of ferroptosis, ultimately alleviating inflammation in treatment of periodontitis.

Proteomic Analysis of the Supernatant from Bone Marrow Mesenchymal Stem Cells under High Glucose Conditions.

Diabetes mellitus hinders the process of bone regeneration by inhibiting the function of mesenchymal stem cells (MSCs) through elevated glucose levels, thereby impeding osteointegration. The stem cell niche (SCN) plays a crucial role in determining the fate of stem cells by integrating various signals. However, the precise mechanism by which high glucose levels affect the SCN and subsequently influence the function of MSCs remains unclear. In this study, we employed proteomic analysis to identify proteins with altered expression in the extracellular matrix (ECM), aiming to elucidate the underlying mechanism. Three cell supernatants were collected from bone marrow mesenchymal stem cells (BMSCs) or BMSCs stimulated with high glucose (BMSCs+Hg). A total of 590 differentially expressed proteins were identified, which were found to be associated with the ECM, including aging, autophagy, and osteogenic differentiation. The findings of our study indicate that elevated glucose levels exert an influence on the molecular aspects of the SCN, potentially contributing to a better comprehension of the underlying mechanism.

Early Diagnosing and Transformation Prediction of Alzheimer's Disease Using Multi-Scaled Self-Attention Network on Structural MRI Images with Occlusion Sensitivity Analysis.

BACKGROUND: Structural magnetic resonance imaging (sMRI) is vital for early Alzheimer's disease (AD) diagnosis, though confirming specific biomarkers remains challenging. Our proposed Multi-Scale Self-Attention Network (MUSAN) enhances classification of cognitively normal (CN) and AD individuals, distinguishing stable (sMCI) from progressive mild cognitive impairment (pMCI). OBJECTIVE: This study leverages AD structural atrophy properties to achieve precise AD classification, combining different scales of brain region features. The ultimate goal is an interpretable algorithm for this method. METHODS: The MUSAN takes whole-brain sMRI as input, enabling automatic extraction of brain region features and modeling of correlations between different scales of brain regions, and achieves personalized disease interpretation of brain regions. Furthermore, we also employed an occlusion sensitivity algorithm to localize and visualize brain regions sensitive to disease. RESULTS: Our method is applied to ADNI-1, ADNI-2, and ADNI-3, and achieves high performance on the classification of CN from AD with accuracy (0.93), specificity (0.82), sensitivity (0.96), and area under curve (AUC) (0.95), as well as notable performance on the distinguish of sMCI from pMCI with accuracy (0.85), specificity (0.84), sensitivity (0.74), and AUC (0.86). Our sensitivity masking algorithm identified key regions in distinguishing CN from AD: hippocampus, amygdala, and vermis. Moreover, cingulum, pallidum, and inferior frontal gyrus are crucial for sMCI and pMCI discrimination. These discoveries align with existing literature, confirming the dependability of our model in AD research. CONCLUSION: Our method provides an effective AD diagnostic and conversion prediction method. The occlusion sensitivity algorithm enhances deep learning interpretability, bolstering AD research reliability.

Detection of Porcine Circovirus Type 3 in Serum, Semen, Oral Fluid, and Preputial Fluid Samples of Boars.

Porcine circovirus type 3 (PCV3) is commonly associated with clinical symptoms such as porcine dermatitis and nephropathy syndrome (PDNS)-like lesions, respiratory signs, and reproductive disorders. This study aimed to investigate the epidemiology of PCV3 in a boar stud. The objectives were to detect PCV3 in semen, as well as matched serum, oral fluid, and preputial fluid samples from adult boars using quantitative polymerase chain reaction (qPCR), analyze PCV3-IgG antibody data, and genetically characterize a positive sample. A total of 112 samples from 28 boars were collected from a large-scale pig farm in Guangxi, China. The qPCR results showed that the PCV3 DNA was not detected in semen, with a positive rate of 0% (0/28), while it was detected in serum (3.57%-1/28), oral fluid (64.28%-18/28), and preputial fluid (46.4%-13/28). The seropositivity rate of PCV3-IgG in serum was 82.14% (23/28) according to the indirect enzyme-linked immunosorbent serologic assay (ELISA) results. Phylogenetic analysis revealed that one of the PCV3 isolates belonged to the PCV3c clades. This is the first report of PCV3 detection in preputial fluid from boars. The results suggest that PCV3 is transmitted among boars on pig farms and exhibits epidemic characteristics.

CENPE and LDHA were potential prognostic biomarkers of chromophobe renal cell carcinoma.

BACKGROUND: Most sarcomatoid differentiated renal cell carcinoma was differentiated from Chromophobe renal cell carcinoma (KICH) and related to a bad prognosis. Thus, finding biomarkers is important for the therapy of KICH. METHODS: The UCSC was used for determining the expression of mRNA and miRNA and clinical data in KICH and normal samples. KEGG and GO were used for predicting potential function of differently expressed genes (DEGs). Optimal prognostic markers were determined by Lasso regression. Kaplan-Meier survival, ROC, and cox regression were used for assessing prognosis value. GSEA was used for predicting potential function of markers. The relations between markers and immune cell infiltration were determined by Pearson method. The upstream miRNA of markers was predicted in TargetScan and DIANA. RESULTS: The 6162 upregulated and 13,903 downregulated DEGs were identified in KICH. Further CENPE and LDHA were screened out as optimal prognostic risk signatures. CENPE was highly expressed while LDHA was lowly expressed in KICH samples, and the high expressions of 2 genes contributed to bad prognosis. The functions of CENPE and LDHA were mainly enriched in proliferation related pathways such as cell cycle and DNA replication. In addition, the correlation of 2 genes with immune infiltrates in KICH was also observed. Finally, we found that has-miR-577 was the common upstream of 2 genes and the binding sites can be predicted. CONCLUSION: CENPE and LDHA were identified as the important prognostic biomarkers in KICH, and they might be involved in the proliferation of cancer cell.

Predicting risk of blastocyst aneuploidy among women with previous aneuploid pregnancy loss: a multicenter-data-based multivariable model.

STUDY QUESTION: Can blastocyst aneuploidy be predicted for patients with previous aneuploid pregnancy loss (PAPL) and receiving preimplantation genetic testing for aneuploidy (PGT-A)? SUMMARY ANSWER: Multivariable logistic regression models were established to predict high risk of blastocyst aneuploidy using four identified factors, presenting good predictive performance. WHAT IS KNOWN ALREADY: Aneuploidy is the most common embryonic chromosomal abnormality leading to pregnancy loss. Several studies have demonstrated a higher embryo aneuploidy rate in patients with PAPL, which has suggested that PGT-A should have benefits in PAPL patients intending to improve their pregnancy outcomes. However, recent studies have failed to demonstrate the efficacy of PGT-A for PAPL patients. One possible way to improve the efficacy is to predict the risk of blastocyst aneuploidy risk in order to identify the specific PAPL population who may benefit from PGT-A. STUDY DESIGN, SIZE, DURATION: We conducted a multicenter retrospective cohort study based on data analysis of 1119 patients receiving PGT-A in three reproductive medical centers of university affiliated teaching hospitals during January 2014 to June 2020. A cohort of 550 patients who had one to three PAPL(s) were included in the PAPL group. In addition, 569 patients with monogenic diseases without pregnancy loss were taken as the non-PAPL group. PARTICIPANTS/MATERIALS, SETTING, METHODS: PGT-A was conducted using single nucleotide polymorphism microarrays and next-generation sequencing. Aneuploidy rates in Day 5 blastocysts of each patient were calculated and high-risk aneuploidy was defined as a rate of ≥50%. Candidate risk factors for high-risk aneuploidy were selected using the Akaike information criterion and were subsequently included in multivariable logistic regression models. Overall predictive accuracy was assessed using the confusion matrix, discrimination by area under the receiver operating characteristic curve (AUC), and calibration by plotting the predicted probabilities versus the observed probabilities. Statistical significance was set at P < 0.05. MAIN RESULTS AND THE ROLE OF CHANCE: Blastocyst aneuploidy rates were 30 ± 25% and 21 ± 19% for PAPL and non-PAPL groups, respectively. Maternal age (odds ratio (OR) = 1.31, 95% CI 1.24-1.39, P < 0.001), number of PAPLs (OR = 1.40, 95% CI 1.05-1.86, P = 0.02), estradiol level on the ovulation trigger day (OR = 0.47, 95% CI 0.30-0.73, P < 0.001), and blastocyst formation rate (OR = 0.13, 95% CI 0.03-0.50, P = 0.003) were associated with high-risk of blastocyst aneuploidy. The predictive model based on the above four variables yielded AUCs of 0.80 using the training dataset and 0.83 using the test dataset, with average and maximal discrepancies of 2.89% and 12.76% for the training dataset, and 0.98% and 5.49% for the test dataset, respectively. LIMITATIONS, REASONS FOR CAUTION: Our conclusions might not be compatible with those having fewer than four biopsied blastocysts and diminished ovarian reserves, since all of the included patients had four or more biopsied blastocysts and had exhibited good ovarian reserves. WIDER IMPLICATIONS OF THE FINDINGS: The developed predictive model is critical for counseling PAPL patients before PGT-A by considering maternal age, number of PAPLs, estradiol levels on the ovulation trigger day, and the blastocyst formation rate. This prediction model achieves good risk stratification and so may be useful for identifying PAPL patients who may have higher risk of blastocyst aneuploidy and can therefore acquire better pregnancy outcomes by PGT-A. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Natural Science Foundation of China under Grant (81871159). No competing interest existed in the study. TRIAL REGISTRATION NUMBER: N/A.

A novel dual-function SERS-based identification strategy for preliminary screening and accurate diagnosis of circulating tumor cells.

Non-specific adsorption of bioprobes based on surface-enhanced Raman spectroscopy (SERS) technology inevitably endows white blood cells (WBC) in the peripheral blood with Raman signals, which greatly interfere the identification accuracy of circulating tumor cells (CTCs). In this study, an innovative strategy was proposed to effectively identify CTCs by using SERS technology assisted by a receiver operating characteristic (ROC) curve. Firstly, a magnetic Fe3O4-Au complex SERS bioprobe was developed, which could effectively capture the triple negative breast cancer (TNBC) cells and endow the tumor cells with distinct SERS signals. Then, the ROC curve obtained based on the comparison of SERS intensity of TNBC cells and WBC was used to construct a tumor cell identification model. The merit of the model was that the detection sensitivity and specificity could be intelligently switched according to different identification purposes such as accurate diagnosis or preliminary screening of tumor cells. Finally, the difunctional recognition ability of the model for accurate diagnosis and preliminary screening of tumor cells was further validated by using the healthy human blood added with TNBC cells and blood samples of real tumor patients. This novel difunctional identification strategy provides a new perspective for identification of CTCs based on the SERS technology.

Expectancy-related changes in firing of dopamine neurons depend on hippocampus.

The orbitofrontal cortex (OFC) and hippocampus (HC) are both implicated in forming the cognitive or task maps that support flexible behavior. Previously, we used the dopamine neurons as a sensor or tool to measure the functional effects of OFC lesions (Takahashi et al., 2011). We recorded midbrain dopamine neurons as rats performed an odor-based choice task, in which errors in the prediction of reward were induced by manipulating the number or timing of the expected rewards across blocks of trials. We found that OFC lesions ipsilateral to the recording electrodes caused prediction errors to be degraded consistent with a loss in the resolution of the task states, particularly under conditions where hidden information was critical to sharpening the predictions. Here we have repeated this experiment, along with computational modeling of the results, in rats with ipsilateral HC lesions. The results show HC also shapes the map of our task, however unlike OFC, which provides information local to the trial, the HC appears to be necessary for estimating the upper-level hidden states based on the information that is discontinuous or separated by longer timescales. The results contrast the respective roles of the OFC and HC in cognitive mapping and add to evidence that the dopamine neurons access a rich information set from distributed regions regarding the predictive structure of the environment, potentially enabling this powerful teaching signal to support complex learning and behavior.

Stimuli-Responsive Codelivery System Self-Assembled from in Situ Dynamic Covalent Reaction of Macrocyclic Disulfides for Cancer Magnetic Resonance Imaging and Chemotherapy.

Supramolecular self-assembly has gained increasing attention to construct multicomponent drug delivery systems for cancer diagnosis and therapy. Despite that these self-assembled nanosystems present surprising properties beyond that of each subcomponent, the spontaneous nature of co-self-assembly causes significant difficulties in control of the synthesis process and consequently leads to unsatisfactory influences in downstream applications. Hence, we utlized an in situ dynamic covalent reaction based on thiol-disulfide exchange to slowly produce disulfide macrocycles, which subsequently triggered the co-self-assembly of an anticancer drug (doxorubicin, DOX) and a magnetic resonance imaging (MRI) contrast agent of ultrasmall iron oxide nanoparticles (IO NPs). It showed concentration regulation of macrocyclic disulfides, DOX, and IO NPs by a dynamic covalent self-assembly (DCS) strategy, resulting in a stable codelivery nanosystem with high drug loading efficiency of 37.36%. More importantly, disulfide macrocycles in the codelivery system could be reduced and broken by glutathione (GSH) in tumor cells, thus leading to disassembly of nanostructures and intellgent release of drugs. These stimuli-responsive performances have been investigated via morphologies and molecular structures, revealing greatly enhanced dual-modal MRI abilities and smart drug release under the trigger of GSH. Moreover, the codelivery system conjugated with a targeting molecule of cyclic Arg-Gly-Asp (cRGD) exhibited significant biocompatibility, MR imaging, and chemotherapeutic anticancer effect in vitro and in vivo. These results indicated that in situ dynamic covalent chemistry enhanced the control over co-self-assembly and paved the way to develop more potential drug delivery systems.